Following the flooding in Manhattan and along the New Jersey shores, Sandy highlighted the need for comprehensive, high-resolution coastal flood modeling solutions. Sandy also provided deeper insights into flood coverage terms and assumptions across various lines of business throughout the insurance industry.

Closed subway station in Lower Manhattan, NY, after Hurricane Sandy hit in 2012

Using RiskLink 13.0, the latest version of our North Atlantic Hurricane model suite, RMS calculated the 100-year return period (RP) surge loss contribution (%) for 12 coastal central business districts, which ranged from Galveston to New York City.

Baltimore and Biloxi are at highest risk, driven by 100-year RP surge contributions of 61% and 51%, respectively, across all lines of business.

Believe it or not, cities like Miami and the Outer Banks in North Carolina exhibited some of the lowest risk against a major surge event, with 100-year RP contributions of 5% each.

Consistent across all high-risk cities:

Located in fairly low-lying areas at or below sea level

Close to shallow-sloping sea beds

These characteristics, among others like wind intensity and angle of landfall, effectively allow for surge to gradually build throughout an approaching storm and impact nearby coastal regions with little or no resistance.

Storm surge damage to a residential structure in Toms River, NJ, as a result of Sandy

In RiskLink 13.0, the RMS view of coastal flood risk remains up-to-date. With the core hazard modeling methodology in place since 2011, RMS has integrated the latest science, data, and industry development into the high-resolution (as high as 180 meters along coastlines and within regions of high exposure densities), hydrodynamic storm surge model from DHI known as MIKE 21.

The inclusion of these updates effectively reduces the uncertainty associated with surge hazard and loss, and ensures that the RMS coastal flood model continues to be the only credible model for quantifying surge risk accurately.

With these advancements and over 30,000 stochastic events that impact the U.S. comes a deeper insight into when and where the next major coastal flood event could occur. For instance, Superstorm Sandy surge losses contributed to 65% of total insured losses.

In RiskLink 13.0, there are over 3,000 stochastic events that do the same, which translates to an annual likelihood of about 10% across all U.S. hurricane states, based on long-term hurricane frequencies. This annual likelihood nearly triples in the Northeast (29%) and doubles in the Gulf (17%), the two regions at highest risk of experiencing the next Sandy-like event.

Similarly, given that a hurricane impacts the U.S., there is a 30% annual chance that the full insured surge loss will exceed $1 billion USD, and nearly a 14% chance that the same losses exceed $5 billion USD.

Regardless of when or where the next major surge event occurs the industry needs to have the right tools available in order to model the magnitude and severity of catastrophic storm surge accurately. For instance, coastal flood models such as MIKE 21 simulate surge characteristics throughout the lifetime of the event, not just at landfall, because it is well known that hurricanes with similar landfalling characteristics do not always produce the same surge risk.

Equally as important is the need for coastal flood models like MIKE 21 to be able to capture the localized nature of key geographical and geological features such as topography, land use, land cover, and bathymetry.

As the industry continues to gain a better understanding of their coastal flood risk landscape, especially on the local scale, RMS will continue to help by incorporating the latest available data and research into our model, investigating the underlying uncertainties and modeling challenges, and investing in future modeling capabilities on RMS(one).

Meteorologist and Manager, Model Product Strategy, RMS
Jeff Waters is a meteorologist who specializes in tropical meteorology, climatology, and general atmospheric science. At RMS, Jeff is responsible for guiding the insurance market’s understanding and usage of RMS models including the North American hurricane, severe convective storm, earthquake, winter storm, and terrorism models. In his role he assists the development of RMS model release communications and strategies, and regularly interacts with rating agencies and regulators around RMS model releases, updates, and general model best practices. Jeff is a member of the American Meteorological Society, the International Society of Catastrophe Managers, and the U.S. Reinsurance Under 40s Group, and has co-authored articles for the Journal of Climate. Jeff holds a BS in geography and meteorology from Ohio University and an MS in meteorology from Penn State University. His academic achievements have been recognized by the National Oceanic and Atmospheric Administration (NOAA) and the American Meteorological Society.